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The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.

Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.

This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.

This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.

This paper discusses the effectiveness of a consortium-based student mobility programme by investigating the impact of the Asian International Mobility for Students (AIMS) Programme. AIMS is a regional multilateral large-scale student mobility programme based on a consortium of 10 member countries and 87 member universities with the Southeast Asian Ministers of Education Organization Regional Centre for Higher Education and Development (SEAMEO RIHED) as a facilitator. Over 6,000 students have participated in a semester-long intra-regional student exchange under AIMS since 2010.

The study employed questionnaire surveys and semi-structured interviews to investigate the impact of AIMS and its advantages as a consortium-based student mobility programme.

It was found that AIMS significantly impacted member universities by accelerating their internationalisation processes through increasing the number of inbound and outbound students and courses offered in English and so on. AIMS has promoted harmonisation among the members by developing common procedures and guidelines, providing platforms for mutual sharing of experiences and good practices and capacity building of international relations offices. AIMS has also had a significant impact on students by enhancing their regional identity and knowledge about the region of Asia, contributing to their development as future regional and global citizens. As advantages of AIMS, member universities efficiently built a foundation for international collaboration with common procedures and guidelines and shared their experiences through such venues as Annual Review Meetings. Students also feel supported by having clear guidance and find programmes prepared by host universities and SEAMEO RIHED useful.

This study is unique in that it empirically studies the impact of one of Asia’s largest student mobility programmes for the first time by analysing large-scale qualitative and quantitative data.

Australia has made impressive efforts over the past two decades in the internationalisation of higher education. Particularly impressive has been the expansion of fee-paying international students. Australia today is the third largest exporter of higher education services internationally, with international students comprising well over 20% of total student enrolments in Australian universities. Expansion of international student enrolments has had major impacts on Australian universities and Australia. On balance, the effects have been strongly positive, producing substantial financial benefits and export income, attracting large number of well-qualified undergraduate and postgraduate students, and leading to a more international orientation for Australia's universities.

Given its growing economic potential and social impact, this study aims to understand the motivations and concerns regarding metaverse usage. It identifies user needs and risks around the metaverse grounded on uses and gratifications theory and perceived risk theory.

The authors analyzed user reviews and rating data from Roblox, a representative modern metaverse platform. They applied BERTopic modeling to extract topics from reviews, identifying key motivations and risk aspects related to metaverse usage. They further constructed an explanatory model to assess how those affect user satisfaction and changes in these effects over time.

This study discovered that gratifications like entertainment, escapism, social interaction and avatar-based self-expression significantly influence user satisfaction in the metaverse. It also highlighted that users find satisfaction in self-expression and self-actualization through creating virtual spaces, items and video content. However, factors such as identity theft, fraud and child safety were identified as potential detriments to satisfaction. These influences fluctuated over time, indicating the dynamic nature of user needs and risk perceptions.

The novelty of this study lies in its dual application of the uses and gratifications theory and perceived risk theory to the metaverse. It provides a novel perspective on user motivations and concerns, shedding light on the distinct elements driving user satisfaction within the metaverse. This study unravels the metaverse’s unique capacity to assimilate features from established digital media while offering a distinctive user-generated experience. This research offers valuable insights for academics and practitioners in digital media and marketing.

This research pioneers the application of both uses and gratifications and perceived risk theories to understand factors influencing metaverse satisfaction. By establishing a comprehensive framework, it explores the metaverse’s unique value as a user-content creation platform, while encompassing existing digital platform characteristics. This study enriches the academic literature on the metaverse and offers invaluable insights for both metaverse platforms and brand marketers.

This study aims to assess the technological capability of Chinese internet platforms (BAT: Baidu, Alibaba, Tencent) compared to US ones (GAFA: Google, Amazon, Facebook, Apple). More specifically, this study explores Baidu’s technological catching-up process with Google by analyzing their patent textual information.

The authors retrieved 26,383 Google patents and 6,695 Baidu patents from PATSTAT 2019 Spring version. The collected patent documents were vectorized using the Word2Vec model first, and then K-means clustering was applied to visualize the technological space of two firms. Finally, novel indicators were proposed to capture the technological catching-up process between Baidu and Google.

The results show that Baidu follows a trend of US rather than Chinese technology which suggests Baidu is aggressively seeking to catch up with US players in the process of its technological development. At the same time, the impact index of Baidu patents increases over time, reflecting its upgrading of technological competitiveness.

This study proposed a new method to analyze technology mapping and evolution based on patent text information. As both US and China are crucial players in the internet industry, it is vital for policymakers in third countries to understand the technological capacity and competitiveness of both countries to develop strategic partnerships effectively.

In Japan, virtual exchange and mobility are regarded as an emergency response to the COVID-19 pandemic and as alternatives to international learning through physical mobility. International educators express concerns that online international learning methods may fade away after physical student mobility resumes on a larger scale. However, it is crucial for universities to leverage newly developed online learning tools after the pandemic in order to offer inclusive international education which reaches the larger student pool who are unable to study abroad. Now is the time to reflect on how international education policy and practice have relied excessively on cross-border student mobility. In turn, it will be important to position ICT-based educational practices as an opportunity to create new value and meaning for international education in an environmentally friendly and low-cost manner in the new normal world. Also, in Japan, internationalization at home was not addressed to any great extent before the pandemic. However, there is an increasing awareness that ICT-based international education can effectively contribute to the expansion of internationalization at home. Adapting to the new normal situation requires a new modality of internationalization, and it will have a significant impact on the attractiveness of higher education in the country.

Automatically extracting stance information from natural language texts is a significant research problem with various applications, particularly after the recent explosion of data on the internet via platforms like social media sites. Stance detection system helps determine whether the author agree, against or has a neutral opinion with the given target. Most of the research in stance detection focuses on the English language, while few research was conducted on the Arabic language.

This paper aimed to address stance detection on Arabic tweets by building and comparing different stance detection models using four transformers, namely: Araelectra, MARBERT, AraBERT and Qarib. Using different weights for these transformers, the authors performed extensive experiments fine-tuning the task of stance detection Arabic tweets with the four different transformers.

The results showed that the AraBERT model learned better than the other three models with a 70% F1 score followed by the Qarib model with a 68% F1 score.

A limitation of this study is the imbalanced dataset and the limited availability of annotated datasets of SD in Arabic.

Provide comprehensive overview of the current resources for stance detection in the literature, including datasets and machine learning methods used. Therefore, the authors examined the models to analyze and comprehend the obtained findings in order to make recommendations for the best performance models for the stance detection task.

The increasing trend for the globalisation of business has highlighted the need for a better understanding of the factors that influence levels of intercultural awareness within organisations. Within the higher education sector, one initiative that aims to address this issue is student study abroad programs. This paper reports on a study that investigates factors that influence Australian students' propensity to engage in these programs. Using both qualitative and quantitative analysis, we examined the role of students' personality in the decision to participate in study abroad programs. The implications for education in international business are discussed.

The purpose of this paper is to clarify the function and issues of intra‐ and inter‐regional cooperation of international higher education in Asia and consider the possibility of East Asian integration as regionalization.

The research consists of two steps. First, by comparing with examples of regional networks and universities’ cooperation programs, it breaks down the current situation of regional cooperation. Second, it analyses the structure of those networks and programs.

Both regional education networks and universities’ cooperation programs develop in multi‐layers and in different phases, and they have a function of distribution of Asian higher education as public goods for regionalization. There are still issues such as immigration control relating to the people's and programs’ mobility, program language, financial and personnel affairs, as well as adjustments to be made in accreditation assessment, credit compatibility and quality assurance including curriculum setting. Retaining the autonomy of countries and higher education agencies in international cooperation is also the major issue in promoting these programs. However, such international cooperation produces the new forms of international higher education for human resource development.

Not all networks and programs can be examined, but the trend and characteristics of the cooperation in higher education can be highlighted.

The findings give significance to the “Campus Asia” concept which is now in preparation for realization by the agreement at the summit of China, Japan and South Korea in October 2009.

While integration and regionalization in East Asia has been discussed previously from the political and economic aspects, this paper responds to the subject from the socio‐cultural aspect by focusing on international higher education in Asia.